Lessons for leaders
Build trust by respecting consumer opinions. Consumers have a solid understanding of AI. They are thinking about the long-term effects, both good and bad. Therefore, the first step is not to underestimate their feelings towards this innovative technology. Marketers and leaders need to be aware of the consumer perspective and ensure that their messages are not too optimistic or ignore consumer concerns. Instead, they must operate and communicate honestly and objectively, balancing the explanation of benefits and risks. In doing so, they build trust.
Brands tend to over-promise and under-deliver. It cannot satisfy this enlightened audience. Rather, marketers and leaders need to be aware of the unknowns and shortcomings when deploying AI tools.
Smartly navigate the curve of misinformation, excitement, and concern. We help organizations counter misinformation, break down misconceptions, and engage people as they deploy public-facing AI tools.
Next, control your excitement and deploy AI using best practices, including responsible AI. Following responsible AI practices that ensure technology is used ethically and responsibly will help, for example, how hyper-personalization can impact privacy, while training AI. It can help reassure consumers and employees who are concerned about things like how data bias is perpetuated. Businesses can strengthen their commitment to responsible AI in their actions and communications.
As your organization expands its use of AI applications, it continues to support consumers and employees and increases trust. At the same time, it will take “transition-ready” steps to protect privacy and reassure and protect consumers and employees from the downside of AI at scale.
Tap the pocket of excitement. Don't think emerging markets are behind when it comes to AI. Consumers in these countries are among the respondents who are excited about this technology and are more likely to adopt it. Global expansion should reflect this trend, rather than following the standard approach of debuting in mature markets. Why not launch an AI product or feature that is especially likely to see widespread and rapid adoption?
There are other reasons why emerging markets are attractive. They have a larger population, which means more customers and more data to drive their solutions. These companies have cost-effective infrastructure and government support, as well as current laws and regulations to enable implementation. Also, while AI models can be expensive and energy-intensive, they may be more cost-effective in emerging markets.
Consumers know more about AI than we imagine and have a more nuanced understanding of it than we realize. This perception depends on the market, how consumers are exposed to AI applications, and their beliefs about how AI could change their lives and livelihoods. It’s important for leaders to keep this understanding in mind if they want to successfully deploy AI at scale.
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